Urban drivers face a daily gamble: circling blocks, misreading signs, and risking tickets â just to park legally. In high-pressure environments like tourist zones, healthcare clinics, and restaurant districts, the cost isnât just financial â itâs missed shifts, late arrivals, decision fatigue, and serious stress. Existing apps focus on static garage listings or paid lots, offering no real help in real-time, curbside parking decisions.
SlotSpot uses real-time data and predictive AI to surface the most legal, convenient parking options â just before arrival. It blends traffic cam data, smart vehicle sensors, GPS, and community input to deliver high-confidence suggestions with visual overlays and voice-ready controls. SlotSpot doesn't just show where to park â it thinks like a driver, adapts like a co-pilot, and gets better every time you use it.
I worked solo as a product designer on this project, making good use of software such as FigJam, Figma, and Illustrator. As well as caffeine.
Dec '24 - May '25
(6 mos. total)
Average annual cost per driver spent searching for parking
Drivers who have avoided trips due to parking difficulties
Time the average driver spends annually searching for a spot
Drivers report feeling stress or anxiety while parking
SlotSpot began where every smart product should â with real users, real environments, and real limitations. I interviewed frustrated commuters, dissected their emotional patterns, and mapped their daily parking decisions. Using empathy mapping and journey analysis, I uncovered the key moments where stress, legality, and trust break down. From there, I audited competitors, identified core opportunity gaps, and translated insights into wireframes that solve actual behavioral pain points. This wasnât just about designing a UI â it was about rebuilding the trust between the driver and the street.
Based on the research, I saw a clear opportunity: simplify legal parking decisions with real-time, safe cues, layered context, and trustworthy design to locate the best parking with easy payment methods.
With clear patterns emerging from interviews and journey mapping, I translated user pain points into product features rooted in real behavior. Drivers like Mike needed voice-controlled rerouting without distraction, while MaryKate prioritized legal curbside parking near vendor zones. I prioritized a predictive AI overlay that adjusts in real time based on traffic, location popularity, and vehicle typeâturning data into action. Every feature I designed was born directly from insights uncovered during research, ensuring that SlotSpot didnât just look smartâit actually helped people park smarter.
Smart Sign Scan
Predictive Spot
Availability
IntegratedÂ
Payments
Map Layer Clarity
Trusted Legal
Information
Parking Zone
Notifications
SlotSpot combines real-time data from multiple sourcesâincluding traffic cameras, Tesla Vision, GPS-based traffic data, and crowdsourced user feedbackâto surface the most legal and likely spots nearby. These inputs are processed by predictive AI to generate smart parking suggestions based on your location, timing, and context. By drawing from these powerful data streams, SlotSpot helps drivers park faster, closer, and with less stress.
This is where the concept became real. I took the insights from real drivers and shaped every screen around fast decision-making, safety, and stress relief. SlotSpotâs UI isnât just meant to be attractiveâitâs made for motion: big tap targets, glanceable info, and timely prompts that show up only when theyâre needed. Each detail reflects a scenario we uncovered in interviews and journey mapping. No fluff. Just what works.
SlotSpot uses dynamic color zones to simplify decision-making in real time. As drivers approach their destination, legal and high-confidence areas are surfaced in green, while caution and restricted zones fade into yellow or redâall without overwhelming the interface.
As the driver nears the destination, SlotSpot highlights available parking zones using a real-time color system. With no taps required, the app visualizes legal optionsâgreen for high-trust areas, yellow for caution, and red for restrictionsâso drivers act instantly and safely.
When the driver changes their route or updates filters mid-trip, SlotSpot instantly recalculates. The zone overlay updates in real time, offering new legal options with minimal disruptionâkeeping parking simple, even when life isnât.
SlotSpot delivers only what fitsâliterally. With filters set, for example,to large spaces within a 5-minute walk, your smart overlay narrows the noise to show safe, spacious options nearby. Less circling, more confidenceâtailored to your vehicle and time.
Unlike typical parking apps, SlotSpot delivers detailed post-drive insightsâtime saved, fuel conserved, and reduced stressâbased on real behavior. By quantifying each success, it shows users the full impact of smarter parking decisions, reinforcing its value through data other apps simply donât offer.
The SlotSpot prototype showcases two streamlined, real-world user flows: onboarding with basic setup, and a live parking session powered by AI-backed data. These demos reflect SlotSpotâs core missionâhelping drivers find legal, convenient parking fast, with clarity and confidence.
The interface overlays smoothly onto familiar maps, using voice-friendly prompts and motion-guided feedback to minimize friction. From walking distance filters to real-time legality checks, the system is optimized for mobile use while parked or en route. Try it out below.
SlotSpot reduces the time, stress, and guesswork of urban parking by translating real-world driver behavior into predictive, actionable suggestions. The AI assistant delivers personalized, legal, and timely results using data from APIs, map systems, and user preferencesâall while maintaining a calm, intuitive interface.
Early feedback showed strong user confidence in the UI and suggestion quality. Participants completed key tasks with minimal friction and praised the systemâs clarity, accuracy, and tone.
Testing is ongoing, but so far has included remote unmoderated usability sessions with three participants completing realistic parking flows using the interactive prototype. Feedback was gathered through follow-up discussions, providing valuable insights reflected in the statistics below. Direct observation testing is scheduled to begin shortly with three additional users who have already been recruited.
The results so far can be summarized as follows:
Estimated Decision Time Reduction
Completed Tasks with Zero Confusion
Reported Increase in Parking Confidence
Said UI Felt Intuitive and Streamlined
SlotSpotâs strongest differentiator is the layered data it draws fromâcombining Tesla vehicle intelligence, GPS movement, traffic cams, and user feedback into one unified system. This fusion is designed to produce spot suggestions that felt accurate, legal, and personalized. Predictive AI makes the app feel like a co-pilot, not just a map.
Please check out more of my case studies below, or reach out to collaborateâI'd love to hear from you!
Please reach out to collaborateâI'd love to hear from you!